A rough-and-ready cluster-based approach for extracting finite-time coherent sets from sparse and incomplete trajectory data | Zendy

Gary Froyland | Zendy; Kathrin PadbergGehle | Zendy

Open Access

A rough-and-ready cluster-based approach for extracting finite-time coherent sets from sparse and incomplete trajectory data

Author(s) -

Gary Froyland,

Kathrin PadbergGehle

Publication year - 2015

Publication title -

chaos an interdisciplinary journal of nonlinear science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.971

H-Index - 113

eISSN - 1089-7682

pISSN - 1054-1500

DOI - 10.1063/1.4926372

Subject(s) - trajectory , cluster analysis , dimension (graph theory) , computer science , algorithm , cluster (spacecraft) , data mining , mathematics , artificial intelligence , physics , astronomy , pure mathematics , programming language

We present a numerical method to identify regions of phase space that are approximately retained in a mobile compact neighbourhood over a finite time duration. Our approach is based on spatio-temporal clustering of trajectory data. The main advantages of the approach are the ability to produce useful results (i) when there are relatively few trajectories and (ii) when there are gaps in observation of the trajectories as can occur with real data. The method is easy to implement, works in any dimension, and is fast to run.

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